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A unified framework for local-ancestry-aware genetic association analysis across biobanks

Hu, L.; Tan, T.; Yuan, K.; Wang, Y.; Gorissen, B. L.; Lin, Y.-S.; Kore, P.; Lu, W.; Mandla, R.; Shi, Z.; Hou, K.; Karczewski, K. J.; Huang, H.; Neale, B. M.; Daly, M. J.; Martin, A. R.; Pasaniuc, B.; Atkinson, E. G.; Zhou, W.

2026-08-11 genetic and genomic medicine
10.64898/2026.08.09.26360047 medRxiv
Show abstract

Biobanks increasingly include individuals with admixed genomes, yet conventional genome-wide association study frameworks either exclude participants who cannot be confidently assigned to a discrete ancestry group or ignore ancestry-specific effects. We present FELIX, a scalable framework for local-ancestry-aware genetic analysis that retains all participants without requiring discrete ancestry assignment. FELIX combines a compact ancestry-resolved genotype representation (FELIXla) with an adaptive association test that jointly evaluates shared-effect and ancestry-specific models at each variant (FELIXassoc). Simulations demonstrated well-calibrated inference under case-control imbalance and power that adapted to the locus-optimal model. Across 24 phenotypes in 240,038 All of Us participants, FELIX analyzed the 12.1% of individuals excluded by global-ancestry clustering and identified 15.4% more genome-wide significant loci than global-ancestry meta-analysis. Additional discoveries arose from recovering ancestry-specific haplotypes carried by admixed participants and from detecting ancestry-dependent marginal effects. Full-cohort effect estimates also improved polygenic score prediction across ancestries and traits.

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